Massively parallel fast elliptic equation solver for three dimensional hydrodynamics and relativity [electronic resource].

Published:: Washington, D.C. : United States. Dept. of Energy, 1995.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description:: 17 pages : digital, PDF file
Additional Creators:: Lawrence Livermore National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information

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Summary:

Through the work proposed in this document we expect to advance the forefront of large scale computational efforts on massively parallel distributed-memory multiprocessors. We will develop tools for effective conversion to a parallel implementation of sequential numerical methods used to solve large systems of partial differential equations. The research supported by this work will involve conversion of a program which does state of the art modeling of multi-dimensional hydrodynamics, general relativity and particle transport in energetic astrophysical environments. The proposed parallel algorithm development, particularly the study and development of fast elliptic equation solvers, could significantly benefit this program and other applications involving solutions to systems of differential equations. We shall develop a data communication manager for distributed memory computers as an aid in program conversions to a parallel environment and implement it in the three dimensional relativistic hydrodynamics program discussed below; develop a concurrent system/concurrent subgrid multigrid method. Currently, five systems are approximated sequentially using multigrid successive overrelaxation. Results from an iteration cycle of one multigrid system are used in following multigrid systems iterations. We shall develop a multigrid algorithm for simultaneous computation of the sets of equations. In addition, we shall implement a method for concurrent processing of the subgrids in each of the multigrid computations. The conditions for convergence of the method will be examined. We`ll compare this technique to other parallel multigrid techniques, such as distributed data/sequential subgrids and the Parallel Superconvergent Multigrid of Frederickson and McBryan. We expect the results of these studies to offer insight and tools both for the selection of new algorithms as well as for conversion of existing large codes for massively parallel architectures.

Report Numbers:

E 1.99:ucrl-id--119803
ucrl-id--119803

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Note:

Published through SciTech Connect.
01/01/1995.
"ucrl-id--119803"
"DE95009385"
Wilson, J.R.; Mathews, G.J.; Sholl, P.L.; Avila, J.H.

Funding Information:

W-7405-ENG-48

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